Managing retention of logs

Abstract

Approaches for managing retention of logs are described. In an example, a log pertaining to an operation and/or development of a product and/or service is obtained. The log is processed to determine log attributes and based on the determined log attributes, a retention criteria specifying a retention period for the log is identified. The identified retention criteria is then applied to maintain the log in a repository. In another example, a request to modify a retention period is received. A conflict between existing and proposed retention criteria is determined based on evaluation factors. If no conflict exists, the new retention period is associated with the log.

What is claimed is: 
     
         1 . A system comprising:
 a processor; and   a machine-readable storage medium comprising instructions executable by the processor to:
 obtain a log pertaining to one of an operation and a development, of one of a product and a service, wherein the one of the operation and the development is implemented using an executable-instructions based system; 
 process the log to determine an attribute pertaining to one of the operation and development; 
 identify, based on the determined attribute, a retention criteria for the log specifying a retention period for retaining the log in a repository; and 
 cause to apply the identified retention criteria for maintaining the log in the repository. 
   
     
     
         2 . The system of  claim 1 , wherein the retention criteria corresponds to a retention factor, the retention factor specifying a category of requirements that are to specify the retention period for the log, and wherein the retention factor comprises conditions pertaining to a regional or location parameter, a regulatory framework, industry practices, performance metric, business needs, storing capabilities, data privacy related conditions, risk related factors, or combination thereof. 
     
     
         3 . The system of  claim 1 , wherein to identify the retention criteria, the instructions are executable to:
 compare a target value corresponding to the attribute of the log, with a corresponding tagged value of the attribute associated with each one of the retention criteria stored in the repository; and   based on the comparison, identify the retention criteria for maintaining the log in the repository.   
     
     
         4 . The system of  claim 1 , wherein a priority factor is associated with the retention criteria based on a relative impact of the retention criteria in relation to the other retention criteria. 
     
     
         5 . The system of  claim 1 , wherein the instructions are executable to:
 obtain a training dataset comprising a log attribute pertaining to a log and corresponding retention criteria, wherein the log attribute comprises at least one of log type, content, source, timestamp, associated product or service, development state, operational context, and regulatory requirements; and   train a machine learning model using the training dataset, wherein the machine learning model, when trained, is to provide a retention criteria for an input log based on log attribute corresponding to the input log.   
     
     
         6 . The system of  claim 5 , wherein the instructions are executable to:
 determine a log attribute for the input log;   input the log attribute into the trained machine learning model to receive a predicted retention criteria as output for maintaining the input log, wherein the predicted retention criteria comprise a retention period, a storage location, and archival requirements; and   apply the predicted retention criteria to the input log for maintaining the input log in the repository.   
     
     
         7 . The system of  claim 1 , wherein the log is one of a batch production record, equipment usage and maintenance logs, quality control text results, product release approvals, corrective and preventive action (CAPA) events, supplier qualification assessment, regulatory submission tracking, adverse events reports, product complaint handling, electronic signature records, formulation change records, clinical trial data entries, stability testing results, method validation documentation, technology transfer activities, design control milestones, risk assessment updates, software validation records, and user equipment specifications. 
     
     
         8 . A method comprising:
 receiving a request from a user to change a first retention period corresponding to a first retention criteria associated with a log, wherein the request comprises a second retention period corresponding to a second retention criteria;   determining a conflict between the first retention criteria and the second retention criteria based on an evaluation factor; and   on determining that the first retention criteria does not conflict with the second retention criteria, associating the second retention period corresponding to the second retention criteria with the log.   
     
     
         9 . The method of  claim 8 , wherein the evaluation factor is one of a priority factor associated with respective retention criteria, user credential of the user, and system capability. 
     
     
         10 . The method of  claim 8 , wherein the determining the conflict comprises:
 comparing the second retention period corresponding to the second retention criteria with the first retention period corresponding to the first retention criteria; and   on determining the second retention period to be different from the first retention period, establishing a conflict between the first retention criteria and the second retention criteria.   
     
     
         11 . The method of  claim 10 , wherein upon establishing the conflict between the first retention criteria and the second retention criteria, the method further comprises:
 comparing a first priority factor, associated with the first retention criteria, and a second priority factor associated with a second retention criteria, wherein the priority factor corresponding to each retention criteria is prescribed based on a relative impact of each retention criteria in relation to the other retention criteria; and   based on the comparison, on determining first priority factor to be greater than the second priority factor, denying the request to alter the first retention period.   
     
     
         12 . The method of  claim 11 , wherein the method further comprises:
 on determining the first priority factor to be less than the second priority factor, associating the second retention period corresponding to the second retention criteria with the log.   
     
     
         13 . The method of  claim 12 , wherein upon determining the first priority factor to be less than the second priority factor, the method further comprises:
 evaluating an impact of the requested change on the operation and development of one of the products and the service; and   based on the evaluation, associating the second retention period corresponding to the second retention criteria with the log.   
     
     
         14 . The method of  claim 13 , wherein to evaluate the impact of the requested change, the method comprises:
 causing to render on a display device, a cost impact based on the evaluation of the impact of the requested changes on an operation and a development of one of a product and a service; and   receiving confirmation from the user, through a user interface rendered on the display device, to proceed with the requested change pursuant to the rendering of cost impact.   
     
     
         15 . The method of  claim 8 , wherein the retention criteria correspond to a retention factor, the retention factor specifying a category of requirements that determines the retention period for the log, wherein the retention factor comprises conditions pertaining to a regional or location parameter, a regulatory framework, industry practices, performance metric, business needs, storing capabilities, data privacy related conditions, risk related factors, or combination thereof. 
     
     
         16 . The method of  claim 8 , wherein upon associating the second retention criteria to the log, the method further comprises:
 determining a current age of the log based on a timestamp indicating origination date and time of the log;   comparing the current age of the log with the second retention period corresponding to the second retention criteria; and   on determining the current age of the log to exceed the second retention period, deleting the log from the repository.   
     
     
         17 . A non-transitory computer-readable medium comprising instructions, the instructions being executable by a processing resource of a system, to:
 monitor a user calendar comprising information related to scheduled audit events to detect changes with respect to audit events, wherein the changes comprise at least one of a scheduling of a new audit event, a modification of an existing audit event, and cancellation of a scheduled audit event;   extract a target retention criteria relevant to the detected changes in the user calendar;   analyze the changes detected in the user calendar to determine a target retention period for the target retention criteria extracted from a repository;   compare the target retention period with an existing retention period of the target retention criteria; and   based on the comparison, alter the existing retention period of the target retention criteria to the target retention period.   
     
     
         18 . The non-transitory computer-readable medium of  claim 17 , wherein the instructions being executable are to:
 on determining the target retention period to exceed or equal to the existing retention period, alter by lengthening the existing retention period to the target retention period; or   on determining the target retention period to be less than the existing retention period, alter by shortening the existing retention period to the target retention period.   
     
     
         19 . The non-transitory computer-readable medium of  claim 17 , wherein to extract a target retention criteria, the instructions being executable are to:
 based on the detected changes, identify a log pertaining to a changed audit event; and   extract, from the repository, the target retention criteria associated with the identified log.   
     
     
         20 . The non-transitory computer-readable medium of  claim 17 , wherein the retention criteria corresponds to a retention factor, the retention factor specifying a category of requirements that determines the retention period for the log, wherein the retention factor comprises conditions pertaining to a regional or location parameter, a regulatory framework, industry practices, performance metric, business needs, storing capabilities, data privacy related conditions, risk related factors, or combination thereof. 
     
     
         21 . A method comprising:
 obtaining, by one or more processors, a log pertaining to one of an operation and a development, of one of a product and a service;   processing, by the one or more processors, the log to determine an attribute pertaining to one of the operation and development;   identifying, based on the determined attribute, a retention criteria for the log specifying a retention period for retaining the log in a repository; and   applying the identified retention criteria for maintaining the log in the repository.   
     
     
         22 . The method of  claim 21 , wherein the retention criteria corresponds to a retention factor, the retention factor specifying a category of requirements that are to specify the retention period for the log, and wherein the retention factor comprises conditions pertaining to a regional or location parameter, a regulatory framework, industry practices, performance metric, business needs, storing capabilities, data privacy related conditions, risk related factors, or combination thereof. 
     
     
         23 . The method of  claim 21 , wherein to identify the retention criteria, the instructions are executable to:
 comparing a target value corresponding to the attribute of the log, with a corresponding tagged value of the attribute associated with each one of the retention criteria stored in the repository; and   based on the comparison, identify the retention criteria for maintaining the log in the repository.   
     
     
         24 . The method of  claim 21 , wherein a priority factor is associated with the retention criteria based on a relative impact of the retention criteria in relation to the other retention criteria. 
     
     
         25 . The method of  claim 21 , wherein the instructions are executable to:
 obtaining a training dataset comprising a log attribute pertaining to a log and corresponding retention criteria, wherein the log attribute comprises at least one of log type, content, source, timestamp, associated product or service, development state, operational context, and regulatory requirements; and   training a machine learning model using the training dataset, wherein the machine learning model, when trained, is to provide a retention criteria for an input log based on log attribute corresponding to the input log.   
     
     
         26 . The method of  claim 25 , wherein the instructions are executable to:
 determining a log attribute for the input log;   inputting the log attribute into the trained machine learning model to receive a predicted retention criteria as output for maintaining the input log, wherein the predicted retention criteria comprise a retention period, a storage location, and archival requirements; and   applying the predicted retention criteria to the input log for maintaining the input log in the repository.   
     
     
         27 . The method of  claim 21 , wherein the log is one of a batch production record, equipment usage and maintenance logs, quality control text results, product release approvals, corrective and preventive action (CAPA) events, supplier qualification assessment, regulatory submission tracking, adverse events reports, product complaint handling, electronic signature records, formulation change records, clinical trial data entries, stability testing results, method validation documentation, technology transfer activities, design control milestones, risk assessment updates, software validation records, and user equipment specifications. 
     
     
         28 . A non-transitory computer-readable medium containing instructions that, when executed by one or more processors, causes the one or more processors to perform operations comprising:
 obtaining, by one or more processors, a log pertaining to one of an operation and a development, of one of a product and a service, wherein the one of the operation and the development is implemented using an executable-instructions based system;   processing, by the one or more processors, the log to determine an attribute pertaining to one of the operation and development;   identifying, based on the determined attribute, a retention criteria for the log specifying a retention period for retaining the log in a repository; and   applying the identified retention criteria for maintaining the log in the repository.   
     
     
         29 . The non-transitory computer-readable medium of  claim 28 , wherein the retention criteria corresponds to a retention factor, the retention factor specifying a category of requirements that are to specify the retention period for the log, and wherein the retention factor comprises conditions pertaining to a regional or location parameter, a regulatory framework, industry practices, performance metric, business needs, storing capabilities, data privacy related conditions, risk related factors, or combination thereof. 
     
     
         30 . The non-transitory computer-readable medium of  claim 28 , wherein to identify the retention criteria, the instructions are executable to:
 comparing a target value corresponding to the attribute of the log, with a corresponding tagged value of the attribute associated with each one of the retention criteria stored in the repository; and   based on the comparison, identify the retention criteria for maintaining the log in the repository.   
     
     
         31 . The non-transitory computer-readable medium of  claim 28 , wherein a priority factor is associated with the retention criteria based on a relative impact of the retention criteria in relation to the other retention criteria. 
     
     
         32 . The non-transitory computer-readable medium of  claim 28 , wherein the instructions are executable to:
 obtaining a training dataset comprising a log attribute pertaining to a log and corresponding retention criteria, wherein the log attribute comprises at least one of log type, content, source, timestamp, associated product or service, development state, operational context, and regulatory requirements; and   training a machine learning model using the training dataset, wherein the machine learning model, when trained, is to provide a retention criteria for an input log based on log attribute corresponding to the input log.   
     
     
         33 . The non-transitory computer-readable medium of  claim 32 , wherein the instructions are executable to:
 determining a log attribute for the input log;   inputting the log attribute into the trained machine learning model to receive a predicted retention criteria as output for maintaining the input log, wherein the predicted retention criteria comprise a retention period, a storage location, and archival requirements; and   applying the predicted retention criteria to the input log for maintaining the input log in the repository.